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What is the future of DevOps in a GPT4 World

GPT4 is here and I was just getting used to GPT3 and the other LLM available – will GPT/LLM change a developers relationship with DevOps dramatically? 

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@code-lightningMar 15.2023 — I do think so, and in a good way. I find myself keeping a ChatGPT window open most days now for quick code troubleshooting or to spark ideas. It's so much faster than Googling and sifting through dozens of sites, or posting to StackOverflow and waiting days only to get a snarky answer from the elites over there.
@td_stacktapeauthorYou spot on Google has now become so time consuming trying to sift through all the results trying to get to the information your after when you just want to ask a question and get an answer. The question is now when will we be able to trust the answer 100%Mar 16.2023
@themolitor"when will we be able to trust the answer 100%" — This is where the developer community is DESPERATELY needed. A good example is our bounty system. We have the same AI language model auto-replying to posted questions with a possible solution. While it does produce good results if the questions are clear, we know it can get it wrong. For that reason, the ai auto-reply can NOT be selected as an answer to the posted bounty. A HUMAN is still needed to either validate the AI response or offer up a better solution. Until ChatGPT can truly think for itself (and pass the turing test), devs are needed now more than ever! 🤘Mar 16.2023(updated)
@td_stacktapeauthorIt will get better over time, and trust is built over time through repeated testing, but as you say for the foreseeable it will need the dev community to build in the checks and balancesMar 17.2023
@themolitorMar 20.2023
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@themolitorMar 15.2023(updated) — Yup. It will for sure. For me it means we'll have more time focusing on the bigger goals of our projects. With v3 I was already spending less time researching methods, bugs, etc. I was also able to put it to work doing more mundane tasks like "smarter" search and replace or having it add certain elements to markup that I would previously have to do manually with the tools I had at my disposal. It has easily cut out a day or two in some cases, which frees me up to move on to the next thing much quicker.
@td_stacktapeauthorThe time savings is real...it's an old saying but time is money and the human race has always been in pursuit of claiming back our time and letting the machines do the mundane time consuming stuff that has to be done but are not high value tasks.Mar 16.2023
@themolitor💯Mar 16.2023
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@Eden WheeleApr 10.2023 — Hii,
I can explain, How the advancement of AI technology, such as the hypothetical GPT-4, could impact the DevOps world. However, it's important to note that GPT-4 doesn't exist yet, and its exact capabilities are still unknown.

That being said, based on the trends of previous AI advancements, it's likely that GPT-4 will have a significant impact on the developer's relationship with DevOps. One of the key benefits of AI technologies is that they can automate many of the routine tasks involved in software development, testing, and deployment.

In the DevOps world, this could mean that AI-powered tools and systems could take over many of the manual processes that currently require human intervention. This could free up developers to focus on more high-level tasks, such as designing and implementing new features, rather than spending time on repetitive and mundane tasks.

However, it's important to note that AI is not a replacement for human skills and expertise. While AI can automate many tasks, it still requires human oversight and intervention to ensure that the software being developed is of high quality and meets the needs of users.

Additionally, the increasing use of AI in DevOps could also lead to new challenges, such as the need to manage and maintain complex AI systems. Developers and DevOps teams will need to stay up-to-date with the latest AI technologies and develop new skills to work effectively with them.

Overall, the future of DevOps in a GPT-4 world is likely to be marked by increased automation, new challenges, and opportunities for developers to focus on high-level tasks.
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@dahliaMay 11.2023 — GPT-4 and other large language models (LLMs) can help developers build more advanced natural language processing (NLP) applications, but they don't directly impact the DevOps process. However, developers working with NLP applications may need to update their skills and workflows to incorporate GPT-4. This could potentially impact their relationship with DevOps teams, who may need to provide support and infrastructure. Overall, the impact of GPT-4 on the developer-DevOps relationship depends on the specific use cases involved and may require closer collaboration between the two teams.


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